title: A computationally designed water-soluble variant of a G-protein-coupled receptor: the human mu opioid receptor.
abstract: G-protein-coupled receptors (GPCRs) play essential roles in various physiological processes, and are widely targeted by pharmaceutical drugs. Despite their importance, studying GPCRs has been problematic due to difficulties in isolating large quantities of these membrane proteins in forms that retain their ligand binding capabilities. Creating water-soluble variants of GPCRs by mutating the exterior, transmembrane residues provides a potential method to overcome these difficulties. Here we present the first study involving the computational design, expression and characterization of water-soluble variant of a human GPCR, the human mu opioid receptor (MUR), which is involved in pain and addiction. An atomistic structure of the transmembrane domain was built using comparative (homology) modeling and known GPCR structures. This structure was highly similar to the subsequently determined structure of the murine receptor and was used to computationally design 53 mutations of exterior residues in the transmembrane region, yielding a variant intended to be soluble in aqueous media. The designed variant expressed in high yield in Escherichia coli and was water soluble. The variant shared structural and functionally related features with the native human MUR, including helical secondary structure and comparable affinity for the antagonist naltrexone (Kd = 65 nM). The roles of cholesterol and disulfide bonds on the stability of the receptor variant were also investigated. This study exemplifies the potential of the computational approach to produce water-soluble variants of GPCRs amenable for structural and functionally related characterization in aqueous solution.
authors.affiliation: Department of Chemistry, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America.
authors.forename: Jose Manuel
authors.initials: JM
authors.lastname: Perez-Aguilar
authors.forename: Jin
authors.initials: J
authors.lastname: Xi
authors.forename: Felipe
authors.initials: F
authors.lastname: Matsunaga
authors.forename: Xu
authors.initials: X
authors.lastname: Cui
authors.forename: Bernard
authors.initials: B
authors.lastname: Selling
authors.forename: Jeffery G
authors.initials: JG
authors.lastname: Saven
authors.forename: Renyu
authors.initials: R
authors.lastname: Liu
mesh_terms: D000595:Amino Acid Sequence; D019943:Amino Acid Substitution; D001667:Binding, Competitive; D019295:Computational Biology; D017076:Computer-Aided Design; D004926:Escherichia coli; D057809:HEK293 Cells; D006801:Humans; D008623:Mercaptoethanol / Q000737:chemistry; D008958:Models, Molecular; D008969:Molecular Sequence Data; D011489:Protein Denaturation; D015202:Protein Engineering; D055550:Protein Stability; D017433:Protein Structure, Secondary; D017434:Protein Structure, Tertiary; D017450:Receptors, Opioid, mu / Q000737:chemistry* / Q000235:genetics; D019163:Reducing Agents / Q000737:chemistry; D012995:Solubility; D012996:Solutions; D014508:Urea / Q000737:chemistry; D014867:Water / Q000737:chemistry
chemical_list: D017450:Receptors, Opioid, mu; D019163:Reducing Agents; D012996:Solutions; D014867:Water; D008623:Mercaptoethanol; D014508:Urea